Soft Computing Techniques for Type-2 Diabetes Data Classification
暫譯: 二型糖尿病數據分類的軟計算技術
Cheruku, Ramalingaswamy, Edla, Damodar Reddy, Kuppili, Venkatanareshbabu
- 出版商: CRC
- 出版日期: 2020-07-27
- 售價: $6,820
- 貴賓價: 9.5 折 $6,479
- 語言: 英文
- 頁數: 152
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 0367236540
- ISBN-13: 9780367236540
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商品描述
Diabetes Mellitus (DM, commonly referred to as diabetes, is a metabolic disorder in which there are high blood sugar levels over a prolonged period. Lack of sufficient insulin causes presence of excess sugar levels in the blood. As a result the glucose levels in diabetic patients are more than normal ones. It has symptoms like frequent urination, increased hunger, increase thirst and high blood sugar. There are mainly three types of diabetes namely type-1, type-2 and gestational diabetes. Type-1 DM occurs due to immune system mistakenly attacks and destroys the beta-cells and Type-2 DM occurs due to insulin resistance. Gestational DM occurs in women during pregnancy due to insulin blocking by pregnancy harmones. Among these three types of DM, type-2 DM is more prevalence, and impacting so many millions of people across the world. Classification and predictive systems are actually reliable in the health care sector to explore hidden patterns in the patients data. These systems aid, medical professionals to enhance their diagnosis, prognosis along with remedy organizing techniques. The less percentage of improvement in classifier predictive accuracy is very important for medical diagnosis purposes where mistakes can cause a lot of damage to patient's life. Hence, we need a more accurate classification system for prediction of type-2 DM. Although, most of the above classification algorithms are efficient, they failed to provide good accuracy with low computational cost. In this book, we proposed various classification algorithms using soft computing techniques like Neural Networks (NNs), Fuzzy Systems (FS) and Swarm Intelligence (SI). The experimental results demonstrate that these algorithms are able to produce high classification accuracy at less computational cost. The contributions presented in this book shall attempt to address the following objectives using soft computing approaches for identification of diabetes mellitus.
- Introuducing an optimized RBFN model called Opt-RBFN.
- Designing a cost effective rule miner called SM-RuleMiner for type-2 diabetes diagnosis.
- Generating more interpretable fuzzy rules for accurate diagnosis of type2 diabetes using RST-BatMiner.
- Developing accurate cascade ensemble frameworks called Diabetes-Network for type-2 diabetes diagnosis.
- Proposing a Multi-level ensemble framework called Dia-Net for improving the classification accuracy of type-2 diabetes diagnosis.
- Designing an Intelligent Diabetes Risk score Model called Intelli-DRM estimate the severity of Diabetes mellitus.
This book serves as a reference book for scientific investigators who need to analyze disease data and/or numerical data, as well as researchers developing methodology in soft computing field. It may also be used as a textbook for a graduate and post graduate level course in machine learning or soft computing.
商品描述(中文翻譯)
糖尿病（Diabetes Mellitus，簡稱 DM，通常稱為糖尿病）是一種代謝性疾病，其特徵是血糖水平在長時間內過高。缺乏足夠的胰島素導致血液中存在過量的糖分。因此，糖尿病患者的葡萄糖水平高於正常人。其症狀包括頻繁排尿、食慾增加、口渴增加和高血糖。糖尿病主要有三種類型，即 1 型、2 型和妊娠糖尿病。1 型 DM 是由於免疫系統錯誤地攻擊並摧毀β細胞所致，而 2 型 DM 則是由於胰島素抵抗所引起。妊娠糖尿病發生在女性懷孕期間，因為妊娠激素阻礙了胰島素的作用。在這三種類型的糖尿病中，2 型 DM 的發病率較高，影響著全球數百萬人。分類和預測系統在醫療保健領域中實際上是可靠的，可以探索患者數據中的隱藏模式。這些系統幫助醫療專業人員提高診斷、預後以及治療組織技術。分類器預測準確性的改善比例較低對於醫療診斷非常重要，因為錯誤可能對患者的生命造成重大損害。因此，我們需要一個更準確的分類系統來預測 2 型 DM。儘管上述大多數分類算法效率高，但它們未能在低計算成本下提供良好的準確性。在本書中，我們提出了各種使用軟計算技術的分類算法，如神經網絡（Neural Networks, NNs）、模糊系統（Fuzzy Systems, FS）和群體智慧（Swarm Intelligence, SI）。實驗結果顯示這些算法能夠在較低的計算成本下產生高分類準確性。本書中提出的貢獻將嘗試使用軟計算方法來識別糖尿病，並達成以下目標：
- 引入一個名為 Opt-RBFN 的優化 RBFN 模型。
- 設計一個名為 SM-RuleMiner 的成本效益規則挖掘器，用於 2 型糖尿病診斷。
- 使用 RST-BatMiner 生成更具可解釋性的模糊規則，以準確診斷 2 型糖尿病。
- 開發名為 Diabetes-Network 的準確級聯集成框架，用於 2 型糖尿病診斷。
- 提出一個名為 Dia-Net 的多層集成框架，以提高 2 型糖尿病診斷的分類準確性。
- 設計一個名為 Intelli-DRM 的智能糖尿病風險評分模型，以評估糖尿病的嚴重程度。
本書作為科學研究人員的參考書，適合需要分析疾病數據和/或數值數據的研究人員，以及在軟計算領域開發方法論的研究者。它也可以用作機器學習或軟計算的研究生和碩士課程的教科書。
作者簡介
Dr. Ramalingaswamy Cheruku is currently working as an Assistant Professor at Dr. Shyama Prasad Mukherjee International Institute of Information Technology, Naya Raipur, India. He has obtained Ph.D. in Computer Science and Engineering from National Institute of Technology Goa, India in 2018. He received B.Tech. degree in CSE from JNT University, Kakinada campus in 2008, M.Tech. degree in CSE from ABV-Indian Institute of Information Technology, Gwalior in 2011. He has served as developer in Tata Consultancy Services for 2 years. He has also published several papers in reputed journals and conferences.
Dr. Damodar Reddy Edla is an Assistant Professor in the department of Computer Science and Engineering at National Institute of Technology Goa, India. He received M.Sc. Degree from University of Hyderabad in 2006, M. Tech. in Computer Application and Ph. D. Degree in Computer Science and Engineering from Indian School of Mines Dhanbad in 2009 and 2013 respectively. His research interests include Cognitive Neuroscience, Data Mining, Wireless Sensor Networks and Brain Computer Interface. He has published more than 90 research articles in reputed journals and International conferences. He is senior member of IEEE and IACSIT. He is also Editorial Board member of several International journals.
Dr. Venkatanareshbabu Kuppili, Ph D (IIT Delhi), is with the Machine Learning Group, Department of CSE, NIT Goa, India, where he is currently an Assistant Professor. He was with Evalueserve pvt. ltd, as a Senior Research Associate. He is also actively involved in teaching and research development for the Graduate Program in Computer Science and Engineering Department at the NIT Goa. He has authored several research papers published in reputed International journals and conferences. He is senior member of IEEE.
作者簡介(中文翻譯)
拉馬林加斯瓦米·切魯庫博士目前擔任印度納亞賴普爾的德·夏雅馬·普拉薩德·穆克吉國際資訊技術學院的助理教授。他於2018年在印度果阿國立技術學院獲得計算機科學與工程博士學位。他於2008年在卡基納達的JNT大學獲得計算機科學與工程的學士學位，並於2011年在古瓦利奧的ABV-印度資訊技術學院獲得計算機科學與工程的碩士學位。他曾在塔塔顧問服務公司擔任開發人員兩年，並在多個知名期刊和會議上發表了數篇論文。
達莫達爾·雷迪·埃德拉博士是印度果阿國立技術學院計算機科學與工程系的助理教授。他於2006年在海德拉巴大學獲得碩士學位，並於2009年和2013年分別在印度礦業學院獲得計算機應用碩士學位和計算機科學與工程博士學位。他的研究興趣包括認知神經科學、資料探勘、無線感測器網路和腦機介面。他在知名期刊和國際會議上發表了超過90篇研究文章。他是IEEE和IACSIT的資深會員，並且是多個國際期刊的編輯委員會成員。
文卡塔納雷什巴布·庫皮利博士（IIT德里博士）目前在印度果阿國立技術學院的計算機科學與工程系的機器學習小組擔任助理教授。他曾在Evalueserve私人有限公司擔任高級研究助理。他還積極參與果阿國立技術學院計算機科學與工程系研究生課程的教學和研究發展。他已發表多篇研究論文於知名國際期刊和會議上，並且是IEEE的資深會員。
